{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "10ccb683",
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import print_function\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.optimize import curve_fit\n",
    "import os, sys, glob\n",
    "# from scipy.signal import savgol_filter\n",
    "%matplotlib inline\n",
    "# import matplotlib as mpl\n",
    "# mpl.rcParams['figure.dpi']=300\n",
    "# mpl.rcParams['mathtext.fontset']='stix'\n",
    "# mpl.rcParams['font.family']='STIXGeneral'\n",
    "from matplotlib.backends.backend_pdf import PdfPages\n",
    "from scipy.integrate import simps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fbe73385",
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_raw(filename,sheetname):\n",
    "    \"\"\"Load the original data into a dataframe\"\"\"\n",
    "    dg = pd.read_excel(filename, sheet_name=sheetname, usecols=['Size', 'Avg_Intensity'])\n",
    "    return dg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "51bbb3f9-f9cd-4451-8ef1-80db10bc3323",
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_raw2(filename,sheetname):\n",
    "    \"\"\"Load the original data into a dataframe\"\"\"\n",
    "    dg=pd.read_excel(filename,header=None,sheet_name=sheetname,names=['Size','Avg_Intensity'],skiprows=1)\n",
    "    return dg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c56dd172",
   "metadata": {},
   "outputs": [],
   "source": [
    "# os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4946e613",
   "metadata": {},
   "outputs": [],
   "source": [
    "# glob.glob(\"**\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fe75759f",
   "metadata": {},
   "outputs": [],
   "source": [
    "d_peg2k=load_raw('Silver_proj.xlsx','PEG2k_Ag10')\n",
    "d_peg5k=load_raw('Silver_proj.xlsx','PEG_5k_Ag10')\n",
    "d_peg20k=load_raw('Silver_proj.xlsx','PEG_20k_AgNP10')\n",
    "d_peg40k=load_raw('Silver_proj.xlsx','PEG_40k_AgNP10')\n",
    "d_peg5k_au=load_raw('Silver_proj.xlsx','PEG5k_Au5')\n",
    "d_ag10=load_raw('Silver_proj.xlsx','Bare_Ag10')\n",
    "d_au5=load_raw('Silver_proj.xlsx','Bare_Au5')\n",
    "\n",
    "d_au10=load_raw('Silver_proj.xlsx','Bare_Au10')\n",
    "d_2kau5=load_raw('Silver_proj.xlsx','PEG_2k_Au5')\n",
    "d_2kau10=load_raw('Silver_proj.xlsx','PEG_2k_Au10')\n",
    "d_5kau10=load_raw('Silver_proj.xlsx','PEG_5k_Au10')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e86f0a19",
   "metadata": {},
   "outputs": [],
   "source": [
    "# d_bare10, d_paa10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "0d733260",
   "metadata": {},
   "outputs": [],
   "source": [
    "xdata = np.asarray(d_peg2k['Size']) #X-axis vlues\n",
    "ydata1 = np.asarray(d_peg5k['Avg_Intensity']) #bare_Au10\n",
    "ydata2 = np.asarray(d_peg20k['Avg_Intensity']) #paa_Au10\n",
    "ydata3 = np.asarray(d_peg40k['Avg_Intensity']) #bare_Au5\n",
    "ydata4 = np.asarray(d_peg5k_au['Avg_Intensity']) #paa_Au5\n",
    "ydata5 = np.asarray(d_ag10['Avg_Intensity']) #cooh5\n",
    "ydata6 = np.asarray(d_au5['Avg_Intensity']) #cooh10\n",
    "ydata7 = np.asarray(d_peg2k['Avg_Intensity']) #cooh10\n",
    "\n",
    "ydata8 = np.asarray(d_au10['Avg_Intensity'])    # For 'Bare_Au10'\n",
    "ydata9 = np.asarray(d_2kau5['Avg_Intensity'])   # For 'PEG_2k_Au5'\n",
    "ydata10 = np.asarray(d_5kau10['Avg_Intensity']) # For 'PEG_5k_Au10'\n",
    "ydata11 = np.asarray(d_2kau10['Avg_Intensity']) # For 'PEG_2k_Au10'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "031e6776",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plt.plot(xdata, ydata1, 'o')\n",
    "# plt.plot(xdata, ydata2, 'o')\n",
    "# plt.plot(xdata, ydata3, 'o')\n",
    "# plt.plot(xdata, ydata4, 'o')\n",
    "plt.plot(xdata, ydata10, 'o', color='black')\n",
    "# plt.plot(xdata, ydata6, 'o')\n",
    "# plt.plot(xdata, ydata7, 'd')\n",
    "plt.xscale('log')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "996eb877",
   "metadata": {},
   "outputs": [],
   "source": [
    "def lognormal(x, A, cen, wid):\n",
    "    return A * np.exp(-(np.log(x) - cen)**2 / (2 * wid**2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c9a97450",
   "metadata": {},
   "outputs": [],
   "source": [
    "def lognormal_sum(x, A1, cen1, wid1, A2, cen2, wid2):\n",
    "    return lognormal(x, A1, cen1, wid1) + lognormal(x, A2, cen2, wid2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "53653733",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a flag to filter the data\n",
    "flag2 = (xdata >= 1e1) & (xdata <= 1e3)\n",
    "flag = (xdata >= 1e1) & (xdata <= 3e2)\n",
    "flag3 = (xdata >= 1e1) & (xdata <= 1e2)\n",
    "flag4 = (xdata >= 1e0) & (xdata <= 0.5e2)\n",
    "# Filter the data using the flag\n",
    "xdata_filtered_1 = xdata[flag]\n",
    "xdata_filtered_2 = xdata[flag2]\n",
    "xdata_filtered_3 = xdata[flag3]\n",
    "xdata_filtered_4 = xdata[flag4]\n",
    "\n",
    "ydata1_filtered = ydata1[flag2]\n",
    "ydata2_filtered = ydata2[flag2]\n",
    "ydata3_filtered = ydata3[flag3]\n",
    "ydata4_filtered = ydata4[flag]\n",
    "ydata5_filtered = ydata5[flag4]\n",
    "ydata6_filtered = ydata6[flag4]\n",
    "ydata7_filtered = ydata7[flag2]\n",
    "\n",
    "\n",
    "ydata8_filtered = ydata8[flag2] \n",
    "ydata9_filtered = ydata9[flag2]  \n",
    "ydata10_filtered = ydata10[flag2]  \n",
    "ydata11_filtered = ydata11[flag2]  \n",
    "\n",
    "plt.plot(xdata_filtered_4, ydata5_filtered, 'o')\n",
    "plt.plot(xdata_filtered_4, ydata6_filtered, 'o')\n",
    "plt.xscale('log')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "364d4c73",
   "metadata": {},
   "outputs": [],
   "source": [
    "popt1, pcov1 = curve_fit(lognormal, xdata_filtered_2, ydata1_filtered) #bare_Au10\n",
    "popt2, pcov2 = curve_fit(lognormal, xdata_filtered_2, ydata2_filtered) #paa_Au10\n",
    "popt3, pcov3 = curve_fit(lognormal, xdata_filtered_3, ydata3_filtered) #bare_Au10\n",
    "popt4, pcov4 = curve_fit(lognormal, xdata_filtered_1, ydata4_filtered) #paa_Au10\n",
    "popt5, pcov5 = curve_fit(lognormal, xdata_filtered_4, ydata5_filtered) #bare_Au10\n",
    "popt6, pcov6 = curve_fit(lognormal, xdata_filtered_4, ydata6_filtered) #paa_Au10\n",
    "popt7, pcov7 = curve_fit(lognormal, xdata_filtered_2, ydata7_filtered) #paa_Au10\n",
    "# Perform curve fitting for ydata8, ydata9, ydata10, and optionally ydata11\n",
    "popt8, pcov8 = curve_fit(lognormal, xdata_filtered_2, ydata8_filtered)  # For Bare_Au10\n",
    "popt9, pcov9 = curve_fit(lognormal, xdata_filtered_2, ydata9_filtered)  # For PEG_2k_Au5\n",
    "popt10, pcov10 = curve_fit(lognormal, xdata_filtered_2, ydata10_filtered)  # For PEG_5k_Au10\n",
    "popt11, pcov11 = curve_fit(lognormal, xdata_filtered_2, ydata11_filtered)\n",
    "\n",
    "x_new = np.linspace(0.1,3000,10000)\n",
    "\n",
    "fit_y1 = lognormal(x_new,  *popt1)\n",
    "fit_y2 = lognormal(x_new,  *popt2)\n",
    "fit_y3 = lognormal(x_new,  *popt3)\n",
    "fit_y4 = lognormal(x_new,  *popt4)\n",
    "fit_y5 = lognormal(x_new,  *popt5)\n",
    "fit_y6 = lognormal(x_new,  *popt6)\n",
    "fit_y7 = lognormal(x_new,  *popt7)\n",
    "\n",
    "fit_y8 = lognormal(x_new, *popt8)\n",
    "fit_y9 = lognormal(x_new, *popt9)\n",
    "fit_y10 = lognormal(x_new, *popt10)\n",
    "# Optionally for ydata11 if it exists\n",
    "fit_y11 = lognormal(x_new, *popt11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "31eba45f-ef71-4b71-bd28-cf72b03cbeb8",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Define colors\n",
    "c1 = 'black' ##Black\n",
    "c2 = 'purple' ##Purple\n",
    "c3 = '#F64C63' ##red\n",
    "c4 = '#4746C2' ##blue\n",
    "c5 = '#29AB87' ##Forest green\n",
    "c6 = '#EF820D' ##Orange F47d43\n",
    "c7 = '#4C86CB' ##Bolt Blue\n",
    "c8 = '#451A00' #Brown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d2e5453e-d44e-47ce-95fa-356f3a4a43e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ydata1 = np.asarray(d_peg5k['Avg_Intensity']) #bare_Au10\n",
    "# ydata2 = np.asarray(d_peg20k['Avg_Intensity']) #paa_Au10\n",
    "# ydata3 = np.asarray(d_peg40k['Avg_Intensity']) #bare_Au5\n",
    "# ydata4 = np.asarray(d_peg5k_au['Avg_Intensity']) #paa_Au5\n",
    "# ydata5 = np.asarray(d_ag10['Avg_Intensity']) #cooh5\n",
    "# ydata6 = np.asarray(d_au5['Avg_Intensity']) #cooh10\n",
    "# ydata7 = np.asarray(d_peg2k['Avg_Intensity']) #cooh10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "ca3a265a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure,ax = plt.subplots(figsize=(6,6))\n",
    "\n",
    "\n",
    "ax.plot(x_new, fit_y7, '-', color=c1, linewidth='3',label='PEG2k-AgNP10')\n",
    "ax.plot(x_new, fit_y1, '-', color=c2,linewidth='3', label='PEG5k-AgNP10')\n",
    "ax.plot(x_new, fit_y5, '--', color=c7,linewidth='3', label='Bare-AgNP10')\n",
    "ax.plot(x_new, fit_y4, '-', color=c3, linewidth='3',label='PEG5k-AuNP5')\n",
    "# ax.plot(x_new, fit_y2, '-', color=c3, linewidth='3',label='PEG20k-AgNP10')\n",
    "# ax.plot(x_new, fit_y3, '-', color=c8,linewidth='3', label='PEG40k-AgNP10')\n",
    "\n",
    "\n",
    "ax.plot(x_new, fit_y6, '-.', color='grey', linewidth='3',label='Bare-AuNP5')\n",
    "ax.plot(x_new, fit_y8, '-.', color='green', linewidth='3',label='Bare-AuNP10')\n",
    "ax.plot(x_new, fit_y9, '-', color=c6, linewidth='3',label='PEG2k-AuNP5')\n",
    "ax.plot(x_new, fit_y10, '-', color=c5, linewidth='3',label='PEG5k-AuNP10')\n",
    "ax.plot(x_new, fit_y11, '-', color=c4, linewidth='3',label='PEG2k-AuNP10')\n",
    "\n",
    "\n",
    "ax.legend(loc='upper center', ncol=2, frameon=True, edgecolor='k',fontsize=13)\n",
    "\n",
    "\n",
    "ax.set_title(\"Hydrodynamic Size Distribution\",fontsize=20)\n",
    "ax.set_xscale('log')\n",
    "ax.set_xlim(4,150)\n",
    "ax.set_ylim(0,33.5)\n",
    "# ax.set_yticks([0,5,10,15,20])\n",
    "ax.tick_params(axis=\"both\",which=\"major\",labelsize=18, direction='in',width=2,length=8) \n",
    "ax.tick_params(axis=\"both\",which=\"minor\",labelsize=18, direction='in',width=1,length=4)\n",
    "ax.set_xlabel('Hydrodynamic Size (d. nm)', fontsize=20)\n",
    "ax.set_ylabel('Intensity (%)',fontsize=20)\n",
    "ax.spines['left'].set_linewidth(2)\n",
    "ax.spines['right'].set_linewidth(2)\n",
    "ax.spines['top'].set_linewidth(2)\n",
    "ax.spines['bottom'].set_linewidth(2)\n",
    "# ax.legend(frameon=True, edgecolor='k',fontsize=12)\n",
    "figure.tight_layout()\n",
    "#figure.savefig('DLS.png',dpi=600)\n",
    "\n",
    "path = 'C:\\\\Users\\\\binay\\\\Box\\\\APS_Ag_Binary\\\\Figures\\\\'\n",
    "PdfPages.savefig(path + 'DLS.pdf',bbox_inches='tight')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f49eaf72-bd9a-4667-ae15-44b58a5f2dc9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ydata1 = np.asarray(d_peg5k['Avg_Intensity']) #bare_Au10\n",
    "# ydata2 = np.asarray(d_peg20k['Avg_Intensity']) #paa_Au10\n",
    "# ydata3 = np.asarray(d_peg40k['Avg_Intensity']) #bare_Au5\n",
    "# ydata4 = np.asarray(d_peg5k_au['Avg_Intensity']) #paa_Au5\n",
    "# ydata5 = np.asarray(d_ag10['Avg_Intensity']) #cooh5\n",
    "# ydata6 = np.asarray(d_au5['Avg_Intensity']) #cooh10\n",
    "# ydata7 = np.asarray(d_peg2k['Avg_Intensity']) #cooh10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8da71023-76f9-44ac-8804-64557ef7a761",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean size for PEG5k-AgNP10: 54.38879099349168, Std Dev: 0.9505460132471502\n",
      "Mean size for PEG20k-AgNP10: 95.4995407961981, Std Dev: 1.3685795616836722\n",
      "Mean size for PEG40k-AgNP10: 114.32252604449594, Std Dev: 1.4131931412785603\n",
      "Mean size for PEG5k-AuNP5: 39.15307636985152, Std Dev: 0.6855428487181077\n",
      "Mean size for Bare-AgNP10: 16.11397971413334, Std Dev: 0.4479203673414944\n",
      "Mean size for Bare-AgNP5: 11.103446176959158, Std Dev: 0.3559502438580405\n",
      "Mean size for PEG2k-AgNP10: 41.26177900621122, Std Dev: 0.802901596072665\n"
     ]
    }
   ],
   "source": [
    "def compute_weighted_mean(y_values, x_values):\n",
    "    return np.average(x_values, weights=y_values)\n",
    "\n",
    "# Bootstrap resampling to calculate the standard deviation of the weighted average size\n",
    "def bootstrap_weighted_mean(y_values, x_values, n_iterations=1000):\n",
    "    means = []\n",
    "    for _ in range(n_iterations):\n",
    "        # Resample with replacement\n",
    "        indices = np.random.choice(range(len(y_values)), len(y_values), replace=True)\n",
    "        resampled_y = y_values[indices]\n",
    "        resampled_x = x_values[indices]\n",
    "        # Sort resampled arrays to maintain the x-order\n",
    "        sorted_indices = np.argsort(resampled_x)\n",
    "        resampled_y = resampled_y[sorted_indices]\n",
    "        resampled_x = resampled_x[sorted_indices]\n",
    "        mean = compute_weighted_mean(resampled_y, resampled_x)\n",
    "        means.append(mean)\n",
    "    return np.mean(means), np.std(means)\n",
    "    \n",
    "# Store all y-values for convenience\n",
    "all_y_values = [fit_y1, fit_y2, fit_y3, fit_y4, fit_y5, fit_y6, fit_y7]\n",
    "\n",
    "# Labels corresponding to each dataset\n",
    "labels = [\n",
    "    'PEG5k-AgNP10',\n",
    "    'PEG20k-AgNP10',\n",
    "    'PEG40k-AgNP10',\n",
    "    'PEG5k-AuNP5',\n",
    "    'Bare-AgNP10',\n",
    "    'Bare-AgNP5',\n",
    "    'PEG2k-AgNP10'\n",
    "]\n",
    "\n",
    "# Calculate mean size and standard deviation using bootstrap for each curve\n",
    "mean_sizes = []\n",
    "std_sizes = []\n",
    "\n",
    "for y_values in all_y_values:\n",
    "    mean_size, std_size = bootstrap_weighted_mean(y_values, x_new)\n",
    "    mean_sizes.append(mean_size)\n",
    "    std_sizes.append(std_size)\n",
    "\n",
    "# Print results\n",
    "for label, mean_size, std_size in zip(labels, mean_sizes, std_sizes):\n",
    "    print(f\"Mean size for {label}: {mean_size}, Std Dev: {std_size}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "3ca72eb6-2dac-4b2a-b347-7deea76da345",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PEG2k: 41.26198553419473 ± 15.873763211570466\n",
      "PEG5k:  54.37148467481001 22.036795170387055\n",
      "PEG20k:  125.19132447913218 48.867763956427716\n",
      "PEG40k:  114.35040170508847 42.91520558857241\n",
      "PEG5k-Au5:  39.142777203372866 10.248455545298858\n",
      "Ag10:  16.09185387958721 4.420663360782359\n",
      "Au5:  11.120963205223191 2.84387509579938\n"
     ]
    }
   ],
   "source": [
    "def calculate_mean_std(x, y):\n",
    "    total_intensity = np.trapz(y, x)\n",
    "    mean_size = np.trapz(y * x, x) / total_intensity\n",
    "    std_dev = np.sqrt(np.trapz(y * (x - mean_size)**2, x) / total_intensity)\n",
    "    return mean_size, std_dev\n",
    "\n",
    "mean1, std1 = calculate_mean_std(x_new, fit_y1)\n",
    "mean2, std2 = calculate_mean_std(x_new, fit_y2)\n",
    "mean3, std3 = calculate_mean_std(x_new, fit_y3)\n",
    "mean4, std4 = calculate_mean_std(x_new, fit_y4)\n",
    "mean5, std5 = calculate_mean_std(x_new, fit_y5)\n",
    "mean6, std6 = calculate_mean_std(x_new, fit_y6)\n",
    "mean7, std7 = calculate_mean_std(x_new, fit_y7)\n",
    "\n",
    "print(f'PEG2k: {mean7} ± {std7}')\n",
    "print(\"PEG5k: \", mean1, std1)\n",
    "print(\"PEG20k: \", mean2, std2)\n",
    "print(\"PEG40k: \", mean3, std3)\n",
    "print(\"PEG5k-Au5: \", mean4, std4)\n",
    "print(\"Ag10: \", mean5, std5)\n",
    "print(\"Au5: \", mean6, std6)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "264e3211-cc08-4a62-bb76-a596ec68fd97",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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